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NLP is logically divided into two processes:

1. Natural Language Understanding (NLU): NLU helps the machine to interpret data for
understanding the meaning of data. It converts text into a machine-readable format.
2. Natural Language Generation (NLG): NLG is a method for creating meaningful
sentences into the natural language. It automatically produces text or speech from structured
data with meaningful phrases and sentences easily understood by humans.

For example, when you ask Google Assistant a question, the words or sentences spoken by you
into the microphone are taken as input. Google Assistant recognises your speech and understands
it with the help of NLU. It then thinks of possible answers with the help of NLG, and gives you
the most relevant one as an output.

Applications of NLP: The following are the different applications of NLP:

Applications
of NLP

• Chatbots: Chatbots are programmed to interact with humans in such a way that they sound
like humans themselves. They are created using NLP and machine learning, which means
they understand language and also learn from their conversations with humans and become
better with time. Chatbots work in two simple steps: first, they identify the meaning of the
question asked and then answer the question appropriately. Example : HDFC bank chatbot.

• Voice Assistants Google Assistant: Siri and Alexa are
common examples of voice assistants that are used to
make calls, place reminders, schedule meetings, browse
the internet, etc. They use NLP to understand what
humans are saying and then act upon it. The goal of voice
assistants is to become a bridge between humans and the
internet to provide services based on just voice

interaction.

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